Can Machine Learning make economic decisions of human quality or better?
Consider managing a memory structure as an economic function.  (Where to put, and how to manage, the resources constituted by data.)  This is something computers can do better and faster than any human.  The reason is that the system in which the economic decisions are being made is fully defined.  

Routing of packages is a similar, economic function that computers do much better than humans.

These functions haven't been handled by Machine Learning in the past, but, soon after the AlphaGo milestone, Google found an economic application for Machine Learning.  Google's DeepMind trains AI to cut its energy bills by 40% (Wired)

So it's entirely context dependent.  

As the model increases in complexity and nuanced, utility will be reduced. (In the former case it's a time and space issue related to computational complexity, and in the latter case, often a function of incomplete information or inability to define parameters.)

But as the sophistication of the machine learning algorithms increases, and the models continue to be refined, the algorithms will get better and better at managing intractability and incomplete information.